Python is one of the most popular tools for analytics or data science, today.
Do you know that In 2013, 21.9% of the developers surveyed said that they had done extensive development work in Python over the past year? By 2022, that number had more than doubled to a whopping 48.1%! This growth is bonkers! And in the world of Python, Pandas library [which stands for Python for Data Analysis] is really a game-changer when it comes to data importing, filtering, wrangling, manipulating, summarizing, or quickly plotting the data. The major story that emerges is that Pandas’ popularity has doubled in the past four years, with a rise from 12.7% to 25.0%.
This is remarkable: Pandas are now as popular as ALL OF PYTHON WAS IN 2016!
This course will make you a pro in using the mighty Pandas for analytics. So are you ready to card up your sleeves to jump into analytics? Do not miss the opportunity to ace the most sought & marketable library, join the course NOW!
This course is designed for:
- Beginners willing to enter Analytics/Data Science/Machine Learning
- Analysts (any domain) wanting to learn Python
- Python developers wanting to learn Analytics/Data Science
- Learners with a passion to explore new areas
Goals
- Using Google Colaboratory to run python code on a virtual machine [without needing to install python]
- Create one or two-dimensional [tabular] data sets in Python Pandas using various methods
- Import & Export external data sets [various file formats like Text, CSV, Excel, HTML, etc.] using Python Pandas
- Filter/Slice data based on indices, names, or using some condition [to answer some questions from the given data set]
- Visualizing data as per the requirement
- Clean Data for missing or invalid values in Pandas
- Explore data to find hidden insights [Typecasting variables, renaming columns, deleting rows/columns, descriptive stats, distribution, Cross tabulation, finding aggregate summaries for different groups & much more]
- Combine multiple data sets [merging/joining or appending similar to various SQL joins and much more]
- Applying your learnings to complete an analytics project.
Prerequisites
- You don't need to have a programming background. You will learn everything you need to know
- You don't need to have a mathematics/statistics background. You will learn everything you need to know
- You just need a passion for learning & love for data crunching
- Basic familiarity with data is a plus
- Basic familiarity with python is a plus [For this you can find free tutorials on my YouTube]